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   <div id="projectname">Reranker Framework (ReFr)
   
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   <div id="projectbrief">Reranking framework for structure prediction and discriminative language modeling</div>
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<div class="title">candidate-set-proto-reader.C</div>  </div>
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<a href="candidate-set-proto-reader_8_c.html">Go to the documentation of this file.</a><div class="fragment"><pre class="fragment"><a name="l00001"></a>00001 <span class="comment">// Copyright 2012, Google Inc.</span>
<a name="l00002"></a>00002 <span class="comment">// All rights reserved.</span>
<a name="l00003"></a>00003 <span class="comment">// </span>
<a name="l00004"></a>00004 <span class="comment">// Redistribution and use in source and binary forms, with or without</span>
<a name="l00005"></a>00005 <span class="comment">// modification, are permitted provided that the following conditions are</span>
<a name="l00006"></a>00006 <span class="comment">// met:</span>
<a name="l00007"></a>00007 <span class="comment">// </span>
<a name="l00008"></a>00008 <span class="comment">//   * Redistributions of source code must retain the above copyright</span>
<a name="l00009"></a>00009 <span class="comment">//     notice, this list of conditions and the following disclaimer.</span>
<a name="l00010"></a>00010 <span class="comment">//   * Redistributions in binary form must reproduce the above</span>
<a name="l00011"></a>00011 <span class="comment">//     copyright notice, this list of conditions and the following disclaimer</span>
<a name="l00012"></a>00012 <span class="comment">//     in the documentation and/or other materials provided with the</span>
<a name="l00013"></a>00013 <span class="comment">//     distribution.</span>
<a name="l00014"></a>00014 <span class="comment">//   * Neither the name of Google Inc. nor the names of its</span>
<a name="l00015"></a>00015 <span class="comment">//     contributors may be used to endorse or promote products derived from</span>
<a name="l00016"></a>00016 <span class="comment">//     this software without specific prior written permission.</span>
<a name="l00017"></a>00017 <span class="comment">//</span>
<a name="l00018"></a>00018 <span class="comment">// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS</span>
<a name="l00019"></a>00019 <span class="comment">// &quot;AS IS&quot; AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT</span>
<a name="l00020"></a>00020 <span class="comment">// LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR</span>
<a name="l00021"></a>00021 <span class="comment">// A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT</span>
<a name="l00022"></a>00022 <span class="comment">// OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,</span>
<a name="l00023"></a>00023 <span class="comment">// SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT</span>
<a name="l00024"></a>00024 <span class="comment">// LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,           </span>
<a name="l00025"></a>00025 <span class="comment">// DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY           </span>
<a name="l00026"></a>00026 <span class="comment">// THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT</span>
<a name="l00027"></a>00027 <span class="comment">// (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE</span>
<a name="l00028"></a>00028 <span class="comment">// OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.</span>
<a name="l00029"></a>00029 <span class="comment">// -----------------------------------------------------------------------------</span>
<a name="l00030"></a>00030 <span class="comment">//</span>
<a name="l00031"></a>00031 <span class="comment">//</span>
<a name="l00036"></a>00036 <span class="comment"></span>
<a name="l00037"></a>00037 <span class="preprocessor">#include &lt;algorithm&gt;</span>
<a name="l00038"></a>00038 <span class="preprocessor">#include &lt;iterator&gt;</span>
<a name="l00039"></a>00039 <span class="preprocessor">#include &lt;set&gt;</span>
<a name="l00040"></a>00040 <span class="preprocessor">#include &lt;tr1/memory&gt;</span>
<a name="l00041"></a>00041 
<a name="l00042"></a>00042 <span class="preprocessor">#include &quot;../proto/data.pb.h&quot;</span>
<a name="l00043"></a>00043 <span class="preprocessor">#include &quot;../proto/model.pb.h&quot;</span>
<a name="l00044"></a>00044 <span class="preprocessor">#include &quot;<a class="code" href="symbol-table_8_h.html" title="Provides the reranker::Symbols interface as well as the reranker::StaticSymbolTable implementation...">symbol-table.H</a>&quot;</span>
<a name="l00045"></a>00045 <span class="preprocessor">#include &quot;<a class="code" href="candidate-set-proto-reader_8_h.html" title="Reads CandidateSetMessage instances and converts them to reranker::CandidateSet instances.">candidate-set-proto-reader.H</a>&quot;</span>
<a name="l00046"></a>00046 
<a name="l00047"></a><a class="code" href="candidate-set-proto-reader_8_c.html#ad72dbcf6d0153db1b8d8a58001feed83">00047</a> <span class="preprocessor">#define DEBUG 0</span>
<a name="l00048"></a>00048 <span class="preprocessor"></span>
<a name="l00049"></a>00049 <span class="keyword">using</span> confusion_learning::CandidateMessage;
<a name="l00050"></a>00050 <span class="keyword">using</span> confusion_learning::CandidateSetMessage;
<a name="l00051"></a>00051 <span class="keyword">using</span> confusion_learning::FeatureVecMessage;
<a name="l00052"></a>00052 <span class="keyword">using</span> confusion_learning::FeatureMessage;
<a name="l00053"></a>00053 <span class="keyword">using</span> confusion_learning::ScoreMessage;
<a name="l00054"></a>00054 
<a name="l00055"></a>00055 <span class="keyword">using</span> std::cout;
<a name="l00056"></a>00056 <span class="keyword">using</span> std::endl;
<a name="l00057"></a>00057 <span class="keyword">using</span> std::insert_iterator;
<a name="l00058"></a>00058 <span class="keyword">using</span> std::ostream_iterator;
<a name="l00059"></a>00059 <span class="keyword">using</span> std::string;
<a name="l00060"></a>00060 <span class="keyword">using</span> std::tr1::unordered_map;
<a name="l00061"></a>00061 <span class="keyword">using</span> std::tr1::shared_ptr;
<a name="l00062"></a>00062 
<a name="l00063"></a>00063 <span class="keyword">namespace </span>reranker {
<a name="l00064"></a>00064 
<a name="l00065"></a>00065 <span class="keywordtype">void</span>
<a name="l00066"></a><a class="code" href="classreranker_1_1_candidate_set_proto_reader.html#a3d58ecb4d9390ec297126ddc4e0bccc7">00066</a> <a class="code" href="classreranker_1_1_candidate_set_proto_reader.html#a210d0ca5accd8310a8dc28d9ace3b76b" title="Fills in the specified CandidateSet based on the specified CandidateSetMessage, crucially constructin...">CandidateSetProtoReader::Read</a>(<span class="keyword">const</span> CandidateSetMessage &amp;m,
<a name="l00067"></a>00067                               <span class="keywordtype">int</span> max_candidates,
<a name="l00068"></a>00068                               <a class="code" href="classreranker_1_1_candidate_set.html" title="A class to hold a set of candidates, either for training or test.">CandidateSet</a> &amp;<span class="keyword">set</span>) {
<a name="l00069"></a>00069   <span class="keywordflow">if</span> (m.has_source_key()) {
<a name="l00070"></a>00070     <span class="keyword">set</span>.set_training_key(m.source_key());
<a name="l00071"></a>00071   }
<a name="l00072"></a>00072   <span class="keywordflow">if</span> (m.has_reference_string()) {
<a name="l00073"></a>00073     <span class="keyword">set</span>.set_reference_string(m.reference_string());
<a name="l00074"></a>00074     <span class="keyword">set</span>.set_reference_string_token_count(CountTokens(<span class="keyword">set</span>.reference_string()));
<a name="l00075"></a>00075   }
<a name="l00076"></a>00076   <span class="keywordflow">if</span> (m.has_gold_index()) {
<a name="l00077"></a>00077     <span class="keyword">set</span>.set_gold_index(m.gold_index());
<a name="l00078"></a>00078   }
<a name="l00079"></a>00079   <span class="keywordflow">if</span> (m.has_best_scoring_index()) {
<a name="l00080"></a>00080     <span class="keyword">set</span>.set_best_scoring_index(m.best_scoring_index());
<a name="l00081"></a>00081   }
<a name="l00082"></a>00082 
<a name="l00083"></a>00083   <span class="keywordtype">int</span> num_candidates = m.candidate_size();
<a name="l00084"></a>00084   <span class="keywordtype">int</span> num_candidates_to_read =
<a name="l00085"></a>00085       max_candidates &lt; 0 ? num_candidates :
<a name="l00086"></a>00086       (max_candidates &gt; num_candidates ? num_candidates : max_candidates);
<a name="l00087"></a>00087   <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; num_candidates_to_read; ++i) {
<a name="l00088"></a>00088     <span class="keyword">const</span> CandidateMessage &amp;candidate_msg = m.candidate(i);
<a name="l00089"></a>00089     <span class="keyword">const</span> FeatureVecMessage &amp;feature_vec_msg = candidate_msg.feats();
<a name="l00090"></a>00090 
<a name="l00091"></a>00091     <a class="code" href="classreranker_1_1_feature_vector.html">FeatureVector&lt;string,double&gt;</a> symbolic_features;
<a name="l00092"></a>00092     <a class="code" href="classreranker_1_1_feature_vector.html">FeatureVector&lt;int,double&gt;</a> features;
<a name="l00093"></a>00093 
<a name="l00094"></a>00094     <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; feature_vec_msg.feature_size(); ++j) {
<a name="l00095"></a>00095       <span class="keyword">const</span> FeatureMessage &amp;feature_msg = feature_vec_msg.feature(j);
<a name="l00096"></a>00096       <span class="keywordflow">if</span> (feature_msg.has_name() &amp;&amp; ! feature_msg.name().empty()) {
<a name="l00097"></a>00097         symbolic_features.<a class="code" href="classreranker_1_1_feature_vector.html#a541f26184a4407f62eb5dad8102cf375" title="Increments the weight of the specified feature by the specified amount.">IncrementWeight</a>(feature_msg.name(),
<a name="l00098"></a>00098                                           feature_msg.value());
<a name="l00099"></a>00099       } <span class="keywordflow">else</span> {
<a name="l00100"></a>00100         features.<a class="code" href="classreranker_1_1_feature_vector.html#a541f26184a4407f62eb5dad8102cf375" title="Increments the weight of the specified feature by the specified amount.">IncrementWeight</a>(feature_msg.id(), feature_msg.value());
<a name="l00101"></a>00101       }
<a name="l00102"></a>00102     }
<a name="l00103"></a>00103     <span class="keywordtype">bool</span> set_loss = <span class="keyword">false</span>;
<a name="l00104"></a>00104     <span class="keywordtype">double</span> <a class="code" href="namespacehadoop-run.html#acccc808b1c10830f49ff1b785c460ddd">loss</a> = 0.0;
<a name="l00105"></a>00105     <span class="keywordtype">double</span> baseline_score = 0.0;
<a name="l00106"></a>00106     <span class="keywordflow">for</span> (<span class="keywordtype">int</span> score_index = 0;
<a name="l00107"></a>00107          score_index &lt; candidate_msg.score_size();
<a name="l00108"></a>00108          ++score_index) {
<a name="l00109"></a>00109       <span class="keyword">const</span> ScoreMessage &amp;score_msg = candidate_msg.score(score_index);
<a name="l00110"></a>00110       <span class="keywordflow">switch</span> (score_msg.type()) {
<a name="l00111"></a>00111         <span class="keywordflow">case</span> ScoreMessage::LOSS:
<a name="l00112"></a>00112           loss = score_msg.score();
<a name="l00113"></a>00113           set_loss = <span class="keyword">true</span>;
<a name="l00114"></a>00114           <span class="keywordflow">break</span>;
<a name="l00115"></a>00115         <span class="keywordflow">case</span> ScoreMessage::SYSTEM_SCORE:
<a name="l00116"></a>00116           <span class="comment">// TODO(dbikel): Deal with the fact that there could be multiple</span>
<a name="l00117"></a>00117           <span class="comment">//               system scores one day, perhaps simply storing</span>
<a name="l00118"></a>00118           <span class="comment">//               them in an array (right now, we just take the</span>
<a name="l00119"></a>00119           <span class="comment">//               last one).</span>
<a name="l00120"></a>00120           baseline_score = score_msg.score();
<a name="l00121"></a>00121           <span class="keywordflow">break</span>;
<a name="l00122"></a>00122         <span class="keywordflow">case</span> ScoreMessage::OUTPUT_SCORE:
<a name="l00123"></a>00123           <span class="keywordflow">break</span>;
<a name="l00124"></a>00124       }
<a name="l00125"></a>00125     }
<a name="l00126"></a>00126 
<a name="l00127"></a>00127     <span class="keywordtype">int</span> num_words = CountTokens(candidate_msg.raw_data());
<a name="l00128"></a>00128 
<a name="l00129"></a>00129     <span class="keywordflow">if</span> (!set_loss) {
<a name="l00130"></a>00130       cerr &lt;&lt; <span class="stringliteral">&quot;CandidateSetProtoReader: warning: computing loss by tokenizing&quot;</span>
<a name="l00131"></a>00131            &lt;&lt; <span class="stringliteral">&quot; and counting.&quot;</span> &lt;&lt; endl;
<a name="l00132"></a>00132       loss = ComputeLoss(<span class="keyword">set</span>, candidate_msg.raw_data());
<a name="l00133"></a>00133     }
<a name="l00134"></a>00134 
<a name="l00135"></a>00135     shared_ptr&lt;Candidate&gt; candidate(<span class="keyword">new</span> <a class="code" href="classreranker_1_1_candidate.html" title="A class to represent a candidate in a set of candidates that constitutes a training instance for a re...">Candidate</a>(i, loss, baseline_score,
<a name="l00136"></a>00136                                                   num_words,
<a name="l00137"></a>00137                                                   candidate_msg.raw_data(),
<a name="l00138"></a>00138                                                   features, symbolic_features));
<a name="l00139"></a>00139     <span class="keyword">set</span>.AddCandidate(candidate);
<a name="l00140"></a>00140   }
<a name="l00141"></a>00141 }
<a name="l00142"></a>00142 
<a name="l00143"></a>00143 <span class="keywordtype">double</span>
<a name="l00144"></a>00144 CandidateSetProtoReader::ComputeLoss(<a class="code" href="classreranker_1_1_candidate_set.html" title="A class to hold a set of candidates, either for training or test.">CandidateSet</a> &amp;<span class="keyword">set</span>,
<a name="l00145"></a>00145                                      <span class="keyword">const</span> <span class="keywordtype">string</span> &amp;candidate_raw_data) {
<a name="l00146"></a>00146   <span class="comment">// For now, find loss for candidate by doing &quot;position-independent WER&quot;.</span>
<a name="l00147"></a>00147   vector&lt;string&gt; ref_toks;
<a name="l00148"></a>00148   tokenizer_.<a class="code" href="classreranker_1_1_tokenizer.html#ab837d52030a12d08faf96217a82f9c8d" title="Tokenizes the specified string, depositing the results into the specified vector.">Tokenize</a>(<span class="keyword">set</span>.reference_string(), ref_toks);
<a name="l00149"></a>00149   vector&lt;string&gt; candidate_toks;
<a name="l00150"></a>00150   tokenizer_.<a class="code" href="classreranker_1_1_tokenizer.html#ab837d52030a12d08faf96217a82f9c8d" title="Tokenizes the specified string, depositing the results into the specified vector.">Tokenize</a>(candidate_raw_data, candidate_toks);
<a name="l00151"></a>00151   std::set&lt;string&gt; ref_toks_set;
<a name="l00152"></a>00152   <span class="keyword">typedef</span> vector&lt;string&gt;::const_iterator const_it;
<a name="l00153"></a>00153   <span class="keywordflow">for</span> (const_it it = ref_toks.begin(); it != ref_toks.end(); ++it) {
<a name="l00154"></a>00154     ref_toks_set.insert(*it);
<a name="l00155"></a>00155   }
<a name="l00156"></a>00156   std::set&lt;string&gt; candidate_toks_set;
<a name="l00157"></a>00157   <span class="keywordflow">for</span> (const_it it = candidate_toks.begin(); it != candidate_toks.end();
<a name="l00158"></a>00158        ++it) {
<a name="l00159"></a>00159     candidate_toks_set.insert(*it);
<a name="l00160"></a>00160   }
<a name="l00161"></a>00161   std::set&lt;string&gt; intersection;
<a name="l00162"></a>00162   insert_iterator&lt;std::set&lt;string&gt; &gt; ii(intersection, intersection.begin());
<a name="l00163"></a>00163   set_intersection(ref_toks_set.begin(), ref_toks_set.end(),
<a name="l00164"></a>00164                    candidate_toks_set.begin(), candidate_toks_set.end(),
<a name="l00165"></a>00165                    ii);
<a name="l00166"></a>00166    
<a name="l00167"></a>00167 
<a name="l00168"></a>00168   <span class="keywordflow">if</span> (<a class="code" href="candidate-set-proto-reader_8_c.html#ad72dbcf6d0153db1b8d8a58001feed83">DEBUG</a>) {
<a name="l00169"></a>00169     ostream_iterator&lt;string&gt; tab_delimited(cout, <span class="stringliteral">&quot;\n\t&quot;</span>);
<a name="l00170"></a>00170     cout &lt;&lt; <span class="stringliteral">&quot;Set of ref toks:\n\t&quot;</span>;
<a name="l00171"></a>00171     copy(ref_toks_set.begin(), ref_toks_set.end(), tab_delimited);
<a name="l00172"></a>00172     cout &lt;&lt; endl;
<a name="l00173"></a>00173     cout &lt;&lt; <span class="stringliteral">&quot;Set of candidate toks:\n\t&quot;</span>;
<a name="l00174"></a>00174     copy(candidate_toks_set.begin(), candidate_toks_set.end(), tab_delimited);
<a name="l00175"></a>00175     cout &lt;&lt; endl;
<a name="l00176"></a>00176     cout &lt;&lt; <span class="stringliteral">&quot;Intersection:\n\t&quot;</span>;
<a name="l00177"></a>00177     copy(intersection.begin(), intersection.end(), tab_delimited);
<a name="l00178"></a>00178     cout &lt;&lt; endl;
<a name="l00179"></a>00179   }
<a name="l00180"></a>00180 
<a name="l00181"></a>00181   <span class="keywordtype">double</span> <a class="code" href="namespacehadoop-run.html#acccc808b1c10830f49ff1b785c460ddd">loss</a> = intersection.size() / (double)ref_toks_set.size();
<a name="l00182"></a>00182 
<a name="l00183"></a>00183   <span class="keywordflow">if</span> (<a class="code" href="candidate-set-proto-reader_8_c.html#ad72dbcf6d0153db1b8d8a58001feed83">DEBUG</a>) {
<a name="l00184"></a>00184     cout &lt;&lt; <span class="stringliteral">&quot;Intersection size is &quot;</span> &lt;&lt; intersection.size()
<a name="l00185"></a>00185          &lt;&lt; <span class="stringliteral">&quot; and there are &quot;</span> &lt;&lt; ref_toks_set.size()
<a name="l00186"></a>00186          &lt;&lt; <span class="stringliteral">&quot; ref toks, so loss is &quot;</span> &lt;&lt; loss &lt;&lt; <span class="stringliteral">&quot;.&quot;</span> &lt;&lt; endl;
<a name="l00187"></a>00187   }
<a name="l00188"></a>00188 
<a name="l00189"></a>00189   <span class="keywordflow">return</span> <a class="code" href="namespacehadoop-run.html#acccc808b1c10830f49ff1b785c460ddd">loss</a>;
<a name="l00190"></a>00190 }
<a name="l00191"></a>00191 
<a name="l00192"></a>00192 }  <span class="comment">// namespace reranker</span>
</pre></div></div><!-- contents -->
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